In recent times the industry has come under immense public scrutiny, with satisfaction among Britain’s train passengers plummeting to an all-time low. The tabloids are rife with talk of soaring fares, late running trains and overcrowding. The latest official national rail passenger satisfaction survey (Autumn 2013) concluded that amongst the train companies included in the survey “none significantly improved and seven were in decline.”
More damning is the dissatisfaction with fare increases. On the worst commuter routes only just over a quarter of the public believe they get value for money from their price of their ticket.
In this context, increased transparency on costs and revenues will be even more important, and it is essential for rail companies to improve their understanding of costs and cost drivers. The main crux for this contention is the general and highly public consensus that UK rail costs are too high, especially when compared to other European countries. Recent studies such as the Rail Value for Money study (May 2011) identified the need to improve value for money and highlighted the significantly high passenger operations costs compared to European comparators.
In understanding potential drivers of costs, there are two main categories to consider
- Cost drivers directly within operators’ control, such as expenditures aimed at increasing revenue
- Cost drivers outside of their direct control, such as inherent market characteristics and franchise specifications.
It is generally accepted that service characteristics vary across the numerous train operating companies (TOC’s), often resulting from market characteristics (topography, demand) and franchise requirements. These service characteristics, along with other factors will drive their costs. The diagram below highlights the type of factors that may influence TOC’s costs and revenues. The factors are sorted by revenues or cost categories and then by how much control TOC’s have on them. The cost drivers listed at the top of boxes are generally cost drivers that TOC’s cannot influence while those listed at the bottom are more under their control.
To compound the increasing complexity of cost analyses and financial modeling, different departments develop their own models and data sets to suit their own needs, thus departing from the universally accepted “a single source of the truth” principle. Many departments are guilty of using disparate spreadsheets and limited performance management solutions that prevent effective cost analysis, and, possibly more importantly, limited capability to scenario plan or quickly re-forecast should market conditions change.
The limitations in terms of analysis and scenario planning result in the inability of Finance/Commercial teams to analyse actual results and identify the business drivers causing variances to budgets and plans. In addition, if actual costs and revenues are not as expected, organizations are unable to swiftly re-plan or re-model forecast data, and invariably end up spending more time trying to explain variances rather than prescribing approaches that may be able to get the actual results on track.
So the question remains; how can rail companies use analytical data to forecast or plan more efficiently?
A strong contender for this is using driver based performance management to establish an effective planning process and enabling a technology solution to provide a seamless link from business drivers through to the outcome results. Driver based performance management provides the means to set targets and manage business drivers that are controlled by the commercial or finance teams. This approach provides more transparency and traceability of actual results thus enabling an effective analysis of variance to latest forecasts and budget.
From a technology angle, the development of an integrated driver based model on a single technology platform provides TOC’s with the opportunity to automate data collection and reporting processes. With less time being taken integrating data, more time can be focused on interrogating cost information and implementing corrective measures where necessary.
The most salient benefit of driver based performance management is the speed at which commercial or finance teams can re-plan by leveraging driver based models. Plans can be quickly recalculated when key assumptions change or when upcoming market changes become apparent.
The increasing volatility, complexity and regulatory focus on the rail industry have made the need for more sophisticated and agile planning and analysis solutions even more apparent in recent years. Improving the way in which TOC’s analyse and forecast data will allow organisations to make quicker and more precise decisions regarding which costs can be controlled, where key revenues are to be made, and how market conditions are affecting performance. It is arguable that implementing driver based solutions would enable ToC’s to focus on the drivers that resonate with the travelling public thereby resulting in a more positive perception of the UK railways.